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Abstract:

A method for determining an irradiation plan includes specifying a target
volume to be irradiated and a condition to be fulfilled, and implementing
a first optimization. Implementing the first optimization includes
providing a first data record, in which the target volume is mapped, and
determining a first parameter set for the irradiation planning by
implementing a first optimization algorithm. The first parameter set is
optimized with respect to the condition to be fulfilled by using the
first data record. The method also includes implementing a second
optimization that includes providing a second data record that has a
higher resolution than the first data record, determining a second
parameter set by implementing a second optimization algorithm. The second
parameter set is optimized with respect to the condition to be fulfilled
by using the second data record and using the first parameter set. The
method also includes generating an irradiation planning data record from
the second parameter set.

Claims:

1. A method for determining an irradiation plan, the method
comprising:specifying a target volume to be irradiated and a condition to
be fulfilled;implementing a first optimization that comprises:providing a
first data record, in which the target volume is mapped;determining a
first parameter set for the irradiation planning by implementing a first
optimization algorithm, in which the first parameter set is optimized
with respect to the condition to be fulfilled using the first data
record;implementing a second optimization that comprises:providing a
second data record, which has a higher resolution than the first data
record;determining a second parameter set for the irradiation planning by
implementing a second optimization algorithm, in which the second
parameter set is optimized with respect to the condition to be fulfilled
using the second data record and the first parameter set; andgenerating
an irradiation planning data record using the second parameter set.

2. The method as claimed in claim 1, wherein implementing the second
optimization comprises determining start values for the second
optimization algorithm from the first parameter set.

3. The method as claimed in claim 1, wherein implementing the first
optimization and implementing the second optimization both comprise
determining, a dose absorbed by the target volume.

4. The method as claimed in claim 3, wherein implementing the first
optimization and implementing the second optimization both comprise
determining an effect of the dose absorbed by the target volume as an
effective dose.

5. The method as claimed in claim 2, wherein implementing the first
optimization and implementing the second optimization both comprise
calculating a particle spectrum generated by a beam to be applied as a
function of the location in the target volume.

6. The method as claimed in claim 5, wherein the particle spectrum
calculated in the first optimization is extrapolated onto the second data
record, which is used in the second optimization step.

7. The method as claimed in claim 5, wherein the start values for the
second optimization algorithm are determined from the particle spectrum
calculated in the first optimization.

8. The method as claimed in claim 1, wherein the method is a planning
method for a scanning method comprising successively controlling a
particle beam to destinations in the target volume, andwherein the first
parameter set and the second parameter set include values that
characterize the number of particles to be applied per destination.

9. The method as claimed in claim 1, wherein the condition to be fulfilled
is a dose distribution to be achieved in the target volume.

10. The method as claimed in claim 1, wherein the first data record and
the second data record are determined from a planning data record.

11. An irradiation planning facility comprising:a computer unit with an
input device and an output device, the computer unit being configured
for:specifying a target volume to be irradiated and a condition to be
fulfilled;implementing a first optimization that comprises:providing a
first data record, in which the target volume is mapped;determining a
first parameter set for the irradiation planning by implementing a first
optimization algorithm, in which the first parameter set is optimized
with respect to the condition to be fulfilled using the first data
record;implementing a second optimization that comprises:providing a
second data record, which has a higher resolution than the first data
record;determining a second parameter set for the irradiation planning by
implementing a second optimization algorithm, in which the second
parameter set is optimized with respect to the condition to be fulfilled
using the second data record and the first parameter set; andgenerating
an irradiation plan data record using the second parameter set.

12. An irradiation system comprising:an irradiation planning facility
comprising a computer unit with an input device and an output device;
anda control apparatus for controlling the irradiation system on the
basis of an irradiation planning data record, the irradiation plan data
record being generated by:specifying a target volume to be irradiated and
a condition to be fulfilled;implementing a first optimization that
comprises:providing a first data record, in which the target volume is
mapped;determining a first parameter set for the irradiation planning by
implementing a first optimization algorithm, in which the first parameter
set is optimized with respect to the condition to be fulfilled using the
first data record;implementing a second optimization that
comprises:providing a second data record, which has a higher resolution
than the first data record;determining a second parameter set for the
irradiation planning by implementing a second optimization algorithm, in
which the second parameter set is optimized with respect to the condition
to be fulfilled using the second data record and the first parameter set;
andgenerating an irradiation plan data record using the second parameter
set.

13. The method as claimed in claim 2, wherein implementing the first
optimization and implementing the second optimization both comprise
determining, a dose absorbed by the target volume.

14. The method as claimed in claim 1, wherein implementing the first
optimization and implementing the second optimization both comprise
calculating a particle spectrum generated by a beam to be applied as a
function of the location in the target volume.

15. The method as claimed in claim 3, wherein implementing the first
optimization and implementing the second optimization both comprise
calculating a particle spectrum generated by a beam to be applied as a
function of the location in the target volume.

16. The method as claimed in claim 4, wherein implementing the first
optimization and implementing the second optimization both comprise
calculating a particle spectrum generated by a beam to be applied as a
function of the location in the target volume.

17. The method as claimed in claim 6, wherein the start values for the
second optimization algorithm are determined from the particle spectrum
calculated in the first optimization.

18. The method as claimed in claim 2, wherein the condition to be
fulfilled is a dose distribution to be achieved in the target volume.

19. The method as claimed in claim 3, wherein the condition to be
fulfilled is a dose distribution to be achieved in the target volume.

20. The method as claimed in claim 8, wherein the condition to be
fulfilled is a dose distribution to be achieved in the target volume.

Description:

[0001]This application claims the benefit of DE 10 2009 040 390.6, filed
on Sep. 7, 2009, which is hereby incorporated by reference.

BACKGROUND

[0002]The present embodiments relate to a method for determining an
irradiation plan.

[0003]Particle therapy is an established method for treating tissue (e.g.,
tumor diseases). Irradiation methods, as are used in particle therapy,
are however also used in non-therapeutic fields. These non-therapeutic
fields include, for example, research work for product development within
the scope of particle therapy, the research work being performed, for
example, on non-living phantoms or bodies or the irradiation of
materials.

[0004]In these applications, charged particles such as, for example,
protons or carbon ions or other ions are accelerated to high energies,
shaped to form a particle beam and guided to one or more irradiation
rooms by way of a high energy beam transportation system. In the
irradiation room, the target volume to be irradiated is irradiated with
the particle beam.

[0005]Irradiation methods referred to as scanning methods are known. With
these methods, a particle beam with a small diameter compared to the
target volume is guided successively to a plurality of destinations in
the target volume; the target volume is "scanned" by the particle beam.

[0006]Methods of "inverse" irradiation planning are likewise known. With
methods of this type, an irradiation target to be reached (e.g., a target
volume to be irradiated, organs to be protected and a target dose to be
achieved) is specified by a user. It is then determined how this
specification can be implemented during an irradiation (i.e., how the
parameters, with which an irradiation process can be controlled and which
finally effect the dose deposition, are to be adjusted). For example, the
dose portion to be applied, the direction from which the dose portion is
to be applied and the area of the target volume to which the dose portion
is to be applied are determined. The parameters that characterize the
dose distribution depend on one another in a complex fashion. An inverse
irradiation planning is thus usually implemented with an optimization
algorithm, which takes these dependencies into account.

SUMMARY AND DESCRIPTION

[0007]The present embodiments may obviate one or more of the drawbacks or
limitations in the related art. For example, in one embodiment, a method
for irradiation planning that allows a rapid calculation of an
irradiation plan, may be specified.

[0008]One embodiment of a method for determining an irradiation plan
includes specifying a target volume to be irradiated and a condition to
be fulfilled and implementing a first optimization. Implementing the
first optimization includes providing a first data record, in which the
target volume is mapped, and determining a first parameter set for the
irradiation planning by implementing a first optimization algorithm. The
first parameter set is optimized with respect to the condition to be
fulfilled by using the first data record. The method also includes
implementing at least one further optimization. Implementing the at least
one further optimization includes providing a further data record that
has a higher resolution than the first data record, determining a further
parameter set for the irradiation planning by implementing a further
optimization algorithm. The further parameter set is optimized with
respect to the condition to be fulfilled by using the further data record
and using the first parameter set. The method also includes generating an
irradiation planning data record from the further parameter set.

[0009]The present embodiments relate to an irradiation planning method, in
which a plurality of optimizations is implemented one after the other.

[0010]The target volume to be irradiated and the condition to be fulfilled
may be specified by a user. The condition to be fulfilled may be a
specification, for example, that characterizes the dose distribution of
the target volume to be achieved and other volumes to be protected.

[0011]The parameter set that is optimized and determined by the
optimizations may be stored in an irradiation planning data record and is
used to control an irradiation system accordingly, so that a
corresponding irradiation of the target volume fulfills the condition to
be fulfilled as well as possible.

[0012]A parameter set of this type may include the number of dose
depositions to be implemented one after the other, the respective beaming
directions and/or the dose to be applied in each instance. With a method
for irradiation planning for a particle beam that is to be applied in the
scanning method, in which the particle beam is to be controlled
successively at several destinations in the target volume, the parameter
set may include values that identify the number of particles to be
applied per destination.

[0013]The parameter set may be used directly or indirectly to control an
irradiation system, depending on the embodiment of the irradiation system
(e.g., after a corresponding interpretation by a control algorithm and
conversion into control commands).

[0014]The optimization acts differ from one another in that the resolution
of the data record, which underlies the respective act, is successively
higher and the calculation and implementation of the optimization acts
thus becomes successively more complex and more expensive.

[0015]The parameter act, which is determined in a preceding optimization
act, may still be determined with comparatively little computing time,
since the resolution of the data record is minimal by comparison with
subsequent steps. In the methods of the present embodiments, this
parameter act is incorporated into the subsequent optimization. An
irradiation planning method designed in this way reaches the target more
rapidly and, despite several optimization acts, with less computing
outlay than methods that use a highly resolved data record from the start
and directly determine the optimum of the parameter values with the aid
of the highly resolved data record.

[0016]The use of the parameter set, which has been determined and
optimized in a previously implemented optimization, is used here to
influence the subsequent optimizations (i.e., to channel and guide the
optimizations in one direction). The optimization algorithm, which is
used in the subsequent optimization, will consequently use fewer
iterations to achieve the target and to determine the optimum for the
parameter set.

[0017]Start values that influence the subsequent optimization may be
determined from the parameter set. These start values already represent a
good approximation of the parameter values that are to be determined and
optimized in the subsequent optimization. Fewer iterations in the
optimization algorithm, when compared with an optimization algorithm
where these start values are not used, are needed in the subsequent
optimization in order to determine the further parameter set. For this
reason, the optimization algorithm may be rapidly implemented even in the
case of a more highly resolved data record, since the start values may be
slightly modified and adjusted.

[0018]The optimization algorithm used in the first optimization and the
further optimization algorithm used in the further optimization may be
the same or different optimization algorithms.

[0019]In one embodiment, a dose absorbed by the target volume may be
determined in the optimization acts. In one embodiment, the condition to
be achieved may also be an absorbed target dose to be achieved. Parameter
values, which are used in one of the optimization acts to determine the
absorbed dose, may be extrapolated to a more highly resolved data record.
The more highly resolved data record is used in one of the subsequent
optimizations.

[0020]The method is advantageous when an effect of the dose absorbed by
the target volume (i.e., an effective dose) is determined in the
optimization acts. In one embodiment, the condition to be achieved may be
a target dose and/or effect on the target volume to be achieved.
Parameter values, which may be used in one of the optimization acts to
determine the effective dose, may be extrapolated to a more highly
resolved data record. The more highly resolved data record is used in one
of the subsequent optimization acts.

[0021]An effect of the particle beam of this type may be characterized by
the relative biological efficiency (RBW). The calculation of the effect
is very computer-intensive (e.g., in the case of particle beams with
particles that are heavier than protons) as a result of the complex
interaction with the target volume. The methods of the present
embodiments, which operate with gradually higher resolutions, may result
in a considerable shortening of the computing time. With the calculation
of the effective dose and/or effect of the dose absorbed by the target
volume, the particle spectrum generated in a position-dependent fashion
by the particle beam is used, for example.

[0022]The parameter set, which is determined and optimized in the
optimization acts, may include further values that are not used directly
or indirectly to control an irradiation system but are used to calculate
the dose distribution to be deposited.

[0023]Parameter values of this type may identify the particle spectrum
that is expected to be generated by the particle beam to be applied. The
generated particle spectrum depends on the anatomy of the target volume
and on the interaction of the particle beam with the anatomy of the
target volume. The generated particle spectrum may also be dependent on a
location (e.g., the generated particle spectrum changes from voxel to
voxel of the data record). The particle spectrum may be calculated
comparatively rapidly with a low-resolution data record, while the
calculation in the case of a higher-resolution data record is
time-consuming and expensive as a result of the complex interaction of
the particle beam with the target volume.

[0024]In one embodiment of the method, a particle spectrum generated by
the beam to be applied is calculated in the optimization acts as a
function of the location in the target volume (e.g., with a resolution
that corresponds to the resolution of the data record that is used in the
respective optimization act). This calculation may take place voxel by
voxel. In the case of a low-resolution data record, the calculation thus
demands less time than with a high-resolution data record.

[0025]The particle spectrum calculated in one of the preceding
optimization acts may be extrapolated to the more highly resolved data
record, which is used in a subsequent optimization act. Start values for
the optimization algorithm may be determined from the particle spectrum
calculated in one of the optimization acts during one of the subsequent
optimization acts (e.g., using the extrapolation). An extrapolation may
be implemented comparatively rapidly and easily.

[0026]In a data record that is used in a preceding optimization act, the
number of voxels is less than the number of voxels of a data record that
is used in one of the subsequent optimization acts. Significant savings
in terms of optimization time result therefrom, since the smaller number
of voxels permits a significantly quicker calculation and implementation
of the optimization algorithm. With this optimization, the particle
spectra occurring in the voxels (e.g., the complete particle spectra) are
calculated. These particle spectra are may be used to calculate the
effect of the particle beam on the target volume in the case of a
particle beam (i.e., the effective dose and/or the relative biological
values). If these particle spectra in each of the voxels are extrapolated
to a higher resolution, very good start values are already predetermined
for the further optimization, which may be implemented on a higher
resolved data record. In the next optimization act, comparatively fewer
iterations are thus used in order to further optimize the parameter set.

[0027]In one embodiment of the method, the data records with different
resolutions, which are used in the optimization acts, are determined from
a single planning data record. This may be a planning CT, for example.
The different data records may be calculated from the single planning
data record by a plurality of adjacent voxels being differently combined
to form a larger voxel, for example using averaging.

[0028]An irradiation planning facility includes a computer unit having an
input device and an output device, with the computer unit being
configured to implement one embodiment of the method for determining an
irradiation plan.

[0029]An irradiation system (e.g., a particle therapy system) includes an
irradiation planning facility of this type and a control apparatus for
controlling the particle therapy system. The particle therapy system may
control the irradiation system using an irradiation planning data record
created according to one embodiment of the method for determining an
irradiation plan.

[0030]Although present embodiments have a particularly advantageous effect
in the case of particle therapy systems, the present embodiments may also
be used with an irradiation using x-ray radiation.

[0031]The preceding and subsequent embodiments relate to features, the
mode of operation and advantages of which relate to the apparatus
category and method category respectively, without this being explicitly
mentioned in each instance. The individual features disclosed here may
also be of significance to the present embodiments in other combinations
than those shown.

BRIEF DESCRIPTION OF THE DRAWINGS

[0032]FIG. 1 shows a schematic representation of a particle therapy
system; and

[0033]FIG. 2 shows a schematic overview of one embodiment of a method for
determining an irradiation plan.

DETAILED DESCRIPTION OF THE DRAWINGS

[0034]FIG. 1 shows a highly schematic representation of a design of an
irradiation system structured as a particle therapy system 10. The
particle therapy system 10 is used to irradiate a target volume, which
may be positioned accordingly with a positioning apparatus, with a beam
including particles (e.g., a particle beam 12). For example, a
tumor-diseased tissue in a patient may be irradiated with the particle
beam 12. The particle beam system 10 may also be used to irradiate a
non-living body (e.g., a water phantom or other phantoms). The
irradiation of the water phantom may take place before and/or after
completion of an irradiation of a patient to monitor and verify
irradiation parameters, for example. Other bodies such as experimental
setups including, for example, cell cultures, or bacteria cultures may
also be irradiated with the particle beam 12.

[0035]The particle therapy system 10 may include a particle source 13 and
an accelerator unit (e.g., a synchrotron 16 and preaccelerator 15 or a
cyclotron or other accelerator), which provides a particle beam 12 with
the energy needed for irradiation purposes. Particles such as protons,
pions, helium ions, carbon ions or ions of other elements may, for
example, be used as particles. A particle beam 12 may, for example, have
a beam diameter of 3-10 mm. The particle beam 12 is guided to an
irradiation room, in which the target volume 14 is located.

[0036]Isoenergy layers 18, 20, 22, 24, 26 and 28 are shown in the target
volume 14 to be irradiated. An isoenergy layer 18, 20, 22, 24, 26 or 28
corresponds, in each case, to the penetration depth of the Bragg peak for
a certain energy of the particle beam 12.

[0037]A raster scan method may be used as a scanning method. In the raster
scan method, the particle beam 12 is guided from one destination 41 to
another destination 41 without having to shut down when transitioning
from one destination to the next. Spot scanning methods with shutdown of
the particle beam may be used between the individual destinations, or
other scanning methods such as, for example, continual scanning methods
may be used. FIG. 1 shows a schematic illustration of the scanning method
with the aid of a plurality of destinations 41. The plurality of
destinations 41 are shown, in part, in the target volume 14 structured
layer-by-layer. The plurality of destinations is reached successively
with the particle beam 12.

[0038]For implementing the scanning method, a scanning apparatus 30 may be
provided with a number of deflection magnets in two orthogonal
directions, which allow the particle beam 12 to be guided from
destination 41 to destination 41.

[0039]A beam monitoring facility 32, with which a beam quality of the
particle beam 12 may be monitored, may include, for example, an
ionization chamber 34 to monitor the number of particles applied by the
particle beam 12 and a location measuring chamber 36 to monitor the
location of the particle beam 12 (measuring apparatuses 34, 36).

[0040]A control facility 38 controls the particle therapy system 10. The
control facility 38 may control the accelerator 15, 16 to provide a beam
with a desired intensity, guide the beam according to an irradiation plan
with the scanning apparatus 30 and evaluate the measurement data of the
beam monitoring facility 32 for monitoring the beam quality. The control
facility 38 may select one of a number of measurement ranges in which the
beam monitoring facility 32 and/or the measuring apparatuses 34, 36
thereof, is to be operated. The control facility 38 may be divided into a
number of sub units that are networked with one another (not shown in
FIG. 1 for simplification).

[0041]An irradiation planning facility 42 (e.g., a computing unit)
includes an input device 44 and an output device 46 for interaction with
a user. The irradiation planning facility 12 is connected to the control
facility 38 such that an irradiation plan, which has been created with
the irradiation planning facility 42, may be executed on the particle
therapy system 10.

[0042]A particle therapy system 10 of this type is known in the prior art.

[0043]An irradiation plan may however be advantageously determined on the
irradiation planning facility 42, if one of the methods of the present
embodiments is executed thereon as explained below.

[0044]FIG. 2 shows a schematic overview of one embodiment of a method for
determining an irradiation plan.

[0045]At act 51, a planning CT is provided. With the aid of a computer
unit, which includes an input device (e.g., a mouse, a keyboard) and an
output device (e.g., monitor), a user of the may mark the target volume
to be irradiated (act 53). The user may also determine in this act which
regions in the object to be irradiated are to be spared, as much as
possible, a dose deposition (e.g., organs at risk (OAR)). The user
specifies a target dose distribution, with which the target volume is to
be irradiated (act 55).

[0046]A first optimization subsequently implemented (act 61). The basis of
this first optimization forms a first data record, which maps the target
volume in a similar fashion to the planning CT. The first data record may
have a significantly smaller resolution than the planning CT (act 62).
The first data record may have been generated from the planning CT, for
example.

[0047]The first data record forms the basis of a first optimization
algorithm, with which the parameters for irradiation are determined and
optimized (act 64).

[0048]The specifications performed by the user with respect to the target
volume and target dose distribution are also incorporated into the first
optimization algorithm. The first optimization algorithm may be a known
optimization algorithm that is already used within the scope of inverse
irradiation planning. An optimization algorithm of this type may be based
on a recursive method.

[0049]A first parameter set for the irradiation plan is optimized with the
first optimization algorithm. This includes, for example, the number of
particles to be applied per destination in the target volume (act 65),
the particle spectrum generated by the particle beam in the target volume
(act 66), the dose absorbed in the target volume (act 67). The first
parameter set may also include the effect generated by the particle beam
in the target volume (the effective dose) (act 68).

[0050]With the first optimization algorithm of the first optimization, the
first parameter set is optimized until the target setting with respect to
the target dose distribution in the target volume is achieved as
accurately as possible. As the first data record has a low resolution,
the first parameter set may not completely fulfill the requirements. A
comparatively small computing time is required herefor, in order to
achieve a first result for the first parameter set with the first
optimization algorithm.

[0051]The first parameter set is further optimized (act 71) in a second
optimization.

[0052]To this end, a second data record is generated from the planning CT,
in which the target volume is likewise mapped. The second data record has
a higher resolution by comparison with the first data record (act 72).

[0053]Similarly to the first optimization, the second data record forms
the basis of the optimization algorithm of the second optimization step.
The specifications of the user with respect to the target volume and the
target dose distribution are incorporated into the optimization algorithm
of the second optimization (act 74). Start values are generated from the
first parameter set, which was determined in the first optimization (act
73). The start values are likewise incorporated into the optimization
algorithm of the second optimization and represent the starting point for
the optimization. Since these values already represent a first
approximation for the parameters to be optimized, the second optimization
algorithm requires comparatively little time and computing power in order
to adjust the first parameter set to the second data record and to find a
second parameter set that better fulfills the specifications of the user
than the first parameter set.

[0054]To generate the start values for the optimization algorithm of the
second optimization, the first parameter set may be extrapolated from the
first optimization onto the second data record (act 81).

[0055]The second parameter set of the second optimization may include
similar parameters to the first parameter set such as, for example, the
number of particles to be applied in the target volume per destination
(act 75), the particle spectrum that is generated by the particle beam in
the target volume (act 76), the dose absorbed in the target volume (act
77) and the effective dose of the particle beam in the target volume (act
78).

[0056]In one embodiment, one or more further optimization step/s may be
implemented similarly to the second optimization (not shown in FIG. 2 for
the sake of simplicity). The optimizations may be repeated and continued
until the optimization on a data record has taken place with a
sufficiently precise resolution. An irradiation plan may be created from
the parameter set that is determined and optimized in this way (act 83).

[0057]It may be inferred from the irradiation plan (e.g., a data record)
how an irradiation has taken place in order to achieve the desired dose
deposition in the target volume. This irradiation plan may be read in and
implemented by the control apparatus of an irradiation system in order to
control the irradiation system for correct irradiation of the target
volume.

[0058]While the present invention has been described above by reference to
various embodiments, it should be understood that many changes and
modifications can be made to the described embodiments. It is therefore
intended that the foregoing description be regarded as illustrative
rather than limiting, and that it be understood that all equivalents
and/or combinations of embodiments are intended to be included in this
description.